1. Field of the Invention
This invention is directed to a method for canceling interferers in a signal using adaptive beamforming, and more specifically to a method of canceling interferers in a broadband active sonar signal using adaptive beamforming.
2. Description of Related Art
Active sonar operates by transmitting a pulse of energy that reflects from targets to a receiver. The receiver may be located proximate the transmitter or may be distant from the transmitter, and more than one receiver can be connected to form an array. The signal received by the receivers includes the reflected pulse of energy, but unwanted returns can also be received in the form of volume reverberation and echoes reflected from the sea bottom and from the water surface. In addition, nearby shipping noise and other sources of underwater noise may be received together with the signal of interest, and could prevent the detection of the desired signal.
A configuration using multiple receivers separated by a certain distance from each other, called an array, can be used to filter out unwanted noise. Since the receivers are separated in space, a signal reaches each different receiver at a different time. The time of arrival is thus dependent on the direction from which the signal originates. For example, if the signal originates from a direction perpendicular to the line of receivers, all the receivers will first receive the signal at the same time. If the signal originates from a direction left of the line of receivers, all the signal will be detected by receiver 1 (the left most receiver) before being detected by the rest of the receivers, this time delay of reception being a function of the signal direction of origin. If one is interested in determining information about a signal arriving perpendicular to the line of receivers, then a simple summation of the data from each receiver, also called a receiver time series, will suffice to obtain all of the signal energy. In general, the signal is not perpendicular, and the time delays must be removed before the receiver data can be summed up in a process called beamforming.
After beamforming, the detected signals originate primarily from a direction of interest, but strong signals from other directions can still be present, although they will be attenuated in strength by the beamformer. The amount of attenuation applied to signals not in the beamformed direction is determined by the array=s beampattern which describes the receiver's response as a function of the direction of the incident sound waves. The beampattern has two main components. One component is a mainlobe, describing the direction of maximum reception, so that signals arriving from that direction are attenuated very little. The second component is the sidelobes, describing the locus of directions of origin from which the signal is attenuated more. Ideally, the sidelobe response should be zero, so that signals arriving from the sidelobe directions can be completely filtered out of the beam. This is not possible in practice. In reality, the sidelobe response for a given acoustic frequency is determined by the number of receivers in the array and by their spacing. The number of receiver elements is limited by cost, since underwater hardware is expensive and only a small number of elements can be deployed practically. Broadband arrays are designed to operate over a broad range of frequencies, but to do so they need many elements to provide low sidelobe response across all of the desired frequencies. However, this design results also in arrays that have high sidelobes in any individual frequency.
Adaptive beamforming improves the conventional beam response by changing the beampattern sidelobes so that the beam response is lower in the direction of strong unwanted sidelobe signals and higher where there is less interference from unwanted signals. This redistribution reduces the noise received on the beam while preserving the strength of the signals received in the direction of interest, enhancing the detectability of desired signals. The shape and size of the sidelobes is changed by weighting the data from each receiver. For example, for 10 receivers, 10 adaptive weights are used.
Since beampatterns change with frequency, adaptive beamforming must be applied separately to each frequency. This is accomplished for broadband signal applications by applying a Fourier Transform to the time series receiver data, which decomposes the broadband signal into a number of narrowband frequencies for which the beampattern is constant. Adaptive beamforming changes the sidelobe pattern on each narrowband frequency independently by weighting each receiver for each frequency differently. Adapted narrowband frequencies are then recombined to produce a broadband adapted beam.
To change the sidelobe patterns, the adaptive beamformer must first estimate the directions of origin of sidelobe signals. When sample matrix inversion approaches are used, the number of samples across time required to calculate the adaptive weights so that they are within 3 dB of the optimal weights for each narrowband frequency, is two times the number of adaptive weights. These time samples must have the same signal structure, meaning that they must have the same direction of arrival and the same strength for the adaptive weights to be optimal over the whole time period being considered. This becomes problematic in the case of adaptive beamforming for active signals, because these signals change rapidly in time.
One class of active signal is a modulated waveform. Modulated waveforms have a long time duration, in the order of a couple of seconds, but when they are matched filtered, their time duration becomes compressed down to the inverse of their bandwidth, which is generally much less than 1 second. Another class of active signal, known as impulsive sources, have by definition a very short time duration.
As noted above, one would like to have narrowband time samples containing the same signal information that can be obtained from modulated signals only by processing them before matched filtering. This apparent solution leads to more difficulties, however, since the unmatched filtered modulated signals have durations so long that they overlap in time with other arriving signals. This can overload the adaptive beamformer as it attempts to process many more simultaneous signals arriving in the sidelobe than necessary. To avoid overloading the adaptive beamformer one is led to match filter the data first and then apply the adaptive beamformer. This leads to time samples having a changing signal content, because the compressed active signals are so short in duration that they are only present within one or two narrowband samples.
One possible solution is to adapt more rapidly and change the adaptive weights every 1 or 2 narrowband samples. In an effort to adapt faster, techniques like beam based adaptive beamforming and dominant mode rejection have been used. Fundamentally, all these techniques require some amount of time samples with consistent signal content to work optimally. One can also combine narrowband frequency samples for the same time sample and use the same adaptive weight across the narrowband frequencies being used. This approach can only be used over a limited fractional bandwidth, since the beampattern and sidelobes are changing across frequency (though more slowly at higher frequencies than at low frequencies). These techniques will perform some amount of averaging of time samples where the signal content is changing. The result is that the sidelobes will be reduced for the entire averaging time rather than only for the time when active signals are actually present. This will null out the active signals but at the price of raising the sidelobe levels in other directions, increasing the overall noise seen on the beam.
A technique described by Anderson in the paper ("Rejection of a coherent arrival at an array", JASA vol. 45, pp. 406-410, 1969) removes broadband sidelobe signals by beamforming in the direction of the sidelobe signals. This produces a good estimate of the interfering signal, which is then subtracted from the original receiver data, effectively removing it. Beamforming is then done on the filtered receiver data to produce beams in the desired directions and with the sidelobe signal removed. This method determines the direction of the sidelobe interferer manually, only one interferer can be removed, and the data processed does not contain any active signals but only passive signals which are basically continuously present.